Biomarkers Reflecting the Severity of Bronchial Asthma in Children.

BACKGROUND

Bronchial asthma, the most prevalent chronic inflammatory airway disease in children, exhibits a concerning rise in both incidence and prevalence. Asthma biomarkers hold promise for stratifying patients into distinct clinical phenotypes, paving the way for targeted and personalized treatment approaches.

AIM OF STUDY

This study aimed to evaluate the association between novel and non-established semi-invasive circulating and well-known exhaled inflammatory biomarkers in two distinct pediatric asthma populations stratified by disease severity.

MATERIALS AND METHODS

Forty-four asthmatic children aged 8-12 years meeting inclusion criteria were recruited from hospitalized patients. The first group (n=15, mean age 9.8 years) consisted of patients with mild persistent asthma who did not require regular inhaled corticosteroids (ICS). The second group (n=29, mean age 9.8 years) consisted of children with moderate to persistent asthma who received regular ICS treatment. Serum levels of interleukins (IL-13, IL-1β), eosinophil-derived neurotoxin (EDN), and surfactant protein D (SPD) were measured by ELISA in all participants. In addition, exhaled nitric oxide (FeNO) and blood eosinophil counts were evaluated.

RESULTS

No significant differences were observed in the baseline plasma concentrations of inflammatory markers (IL-13, IL-1β, SPD, and EDN) or exhaled FeNO between the ICS-treated and non-ICS-treated groups. Further inter-individual analysis confirmed significant positive correlations between IL-13, SPD, and IL-1β (Pearson's r = 0.591-0.781) in both groups of patients. Interestingly, the ICS-treated group compared to the nontreated group showed an exclusive moderate negative correlation between FeNO and IL-1β. In contrast, FeNO exhibited a positive correlation with EDN and a strong association with eosinophil count in all the study groups.

CONCLUSION

Our findings highlight the complex and unresolved role of asthma biomarkers in routine clinical practice for the management of childhood asthma, particularly in predicting exacerbations. By comparing the relationships of carefully selected biomarkers, we can achieve a greater clinical predictive value.